Can Crowdsourcing Prevent Credit Card Fraud?

Yaron Samid believes the best way to combat credit card fraud and errors is not just to use data, but use lots of it. Samid’s start-up BillGuard, just came out of stealth mode and is looking to build a fraud protection system that leverages a consumer’s own data history along with signals gathered online and through banks. By constructing smart algorithms that digests complicated transactional information and pulls in alerts from both existing members and the web, BillGuard believes it can build a crowd-sourced anti-virus system for bills.

The idea has won the New York company $3 million in angel funding from Ron Conway, Chris Dixon, Howard Lindzon, Bessemer Ventures, IA Ventures and Yaron Galai. And BillGuard, which also has a research and development office in Israel, was recognized as the top start-up at the Strata data conference last week. This is the latest start-up for CEO and co-founder Samid, who previously co-founded Pando Networks, a scaleable content delivery solution. Raphael Ouzan, a big data mining and security expert, is the other co-founder.

BillGuard works like this: consumers register their credit and debit card accounts with BillGuard, which ingests all the transaction information and organizes it in one database. The company will allow users to flag each transaction for questions, errors or fraud. Those user alerts will get combined with other bank data and notices on recent fraud activity along with web chatter from Twitter and consumer forums. Customers will then get notified via e-mail if they have a questionable, fraudulent or erroneous charge on their credit cards.

For the vast majority of credit card users who don’t scrutinize every transaction, BillGuard brings an extra level of protection. Even power users who check every bill can benefit: BillGuard provides added peace of mind and also the ability to share the fruits of their vigilance with others. It’s not just for fraud but it also addresses merchants who pack in extra charges on to bills knowing that most consumers often won’t notice.

“We’re discovering lots of possibilities by crowdsourcing consumer vigilance,” said Samid in a phone interview. “Its an entirely new data-set that we’re structuring but the real IP is the back-end algorithms that make that data actionable. We’re training computers to understand the language of transactions. It’s a lot of messy data coming from the banks.”

Banks already have fraud protection, but Samid said much of that involves broad pattern detection that often can’t uncover more complex schemes or persistant errors. For example, Samid said his debit card number last month fell into the hands of scammers, who quietly placed a legitimate looking $8.95 charge on his card. BillGuard looked up the transaction information and when it couldn’t identify the merchant online, flagged the payment, allowing Samid to correct the situation.

BillGuard is currently in alpha with friends and family and is looking to open up to a beta in the second quarter with a more fuller featured offering. The company has not announced pricing but Samid said there will be a freemium model, so users will be able to try at least some of the services for free. He said while a standalone service will always be available, BillGuard has been talking to banks and financial institutions, who are receptive to the idea of incorporating BillGuard into their online services.

BillGuard is a good example of the ways companies can take small bits of consumer information and apply big data techniques of analysis, visualization and machine learning to create valuable services. The company will need to get consumers to agree to hand over their financial data, which could be affected by how much the premium services costs and how much they trust BillGuard’s security. And the service’s effectiveness may be somewhat dependent on its ability to recruit hyper vigilant users, who can flag transactions that benefit the entire user base. But if BillGuard can scale up and tap into a large customer base, it could be a very powerful way to help combat online fraud, not just for bank and credit card bills but a wide variety of billing services. If you’re interested in big data, GigaOM will be hosting its first annual Structure Big Data conference in New York March 23.